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Credibility Evaluation of Simulation Models Using Group Analytic Hierarchy Process Based on Priority Probability Conversion

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Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 646))

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Abstract

The credibility evaluation of models has attracted extensive attention in Modeling and Simulation (M&S). With increasingly complex models, multiple domain experts are required to jointly assess the credibility of a model. Group analytic hierarchy process (GAHP) is a method by many experts to make decision. In GAHP, the preference aggregation of group members is a critical procedure. However, the impact of expert number and indicator priority order on the evaluation results has not been well considered in previous preference aggregation procedure yet. In this paper, we first propose a novel preference aggregation procedure, priority probability conversion (PPC), to enhance the effectiveness of GAHP, named PPC-GAHP. Then, we introduce a commonly used evaluation criteria for such procedures. Finally, a numerical example is provided to elucidate the details of the proposed procedure and is compared with other aggregation procedures in GAHP to further demonstrate its validity.

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Acknowledgments

Authors gratefully acknowledge the support of National Natural Science Foundation of China under Grant No. 61374199, Natural Science Foundation of Beijing under Grant No. 4142031 and National High-Tech Research and Development Plan of China under Grant No. 2013AA041302.

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Correspondence to Lin Zhang .

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Yang, G., Laili, Y., Zhang, L., Hu, X. (2016). Credibility Evaluation of Simulation Models Using Group Analytic Hierarchy Process Based on Priority Probability Conversion . In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 646. Springer, Singapore. https://doi.org/10.1007/978-981-10-2672-0_52

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  • DOI: https://doi.org/10.1007/978-981-10-2672-0_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2671-3

  • Online ISBN: 978-981-10-2672-0

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